Active traffic management: adaptive traffic signal control

Active traffic management (ATM) uses advanced technologies (computing, communication, and electronics) and traffic management centers to improve roadway traffic flow. Adaptive traffic signal control is an ATM solution for reducing traffic congestion through intersection signal (traffic light) optimization using real-time data. The essential components of the control system are roadside traffic sensors, a central computer (control center), traffic-signal controllers at the intersections, and a fiber-optic or wireless communication system. In recent years, Los Angeles and New York City have made significant investments in upgrading their traffic signals to adaptive control. See also: Active traffic management;
Data communications;
Highway engineering;
Optimal control theory;
Optimization;
Traffic-control systems;
Ubiquitous transportation network sensors

Los Angeles’s Automated Traffic Surveillance and Control System (ATSAC) consists of 4400 remotely controlled traffic signals. Inductive (magnetic) loop sensors embedded in the roadway measure the traffic volume at intersections and send the data to a control center, where the data are analyzed and signal timing can be adjusted automatically by computer software or manually by an operator to minimize congestion. ATSAC also has 400 closed-circuit television (CCTV) cameras so that operators can observe how traffic is moving throughout the city. Early reports indicate that the system has produced about a 16% increase in travel speed. See also: Closed-circuit television (CCTV); Software

By the end of 2013, the New York City Department of Transportation (NYCDOT) had upgraded all of its 12,500 traffic signals with Advanced Solid-state Traffic Signal Controllers (ASTC) and installed about 250 CCTV cameras in its five boroughs. In midtown Manhattan—between First and Ninth Avenues and from 42nd to 57th Streets, the most congested area of the city—210 microwave sensors, 56 video cameras, and 59 E-ZPass® readers (to measure traffic speed) have been installed above the roadway. Setup of the program known as Midtown in Motion was completed in 2012. As in Los Angles, signal timing can be adjusted at the control center by software or operators. Improvements in travel speed of up to 10% have been reported. See also: RFID in transportation and logistics

Critics of these systems say that a 10–16% improvement of a very slow traffic speed is barely noticeable. Moreover, they argue, if a speed-up in traffic is generally recognized, it will counterproductively encourage more people to drive their vehicles. Skepticism aside, however, over the long term even small increases in speed add up to significant numbers in terms of vehicle trip times, fuel consumption, and greenhouse-gas emissions. See also: Transportation's role in sustainability

Looking toward the future, in a project known as SURTRAC (Scalable Urban Traffic Control), researchers at Carnegie Mellon University in Pittsburgh, Pennsylvania, used artificial intelligence and transportation engineering principles to develop a software system that allows neighboring traffic signals to communicate with one another and to adapt to traffic conditions on a second-by-second basis. The system was pilot-tested at nine intersections in Pittsburgh’s East Liberty district, a commercial and business center, and resulted in reductions of 25% in travel times and 21% in vehicle emissions. The SURTRAC technology is expected to cost $50,000 to $75,000 per intersection. Nevertheless, if Los Angeles had been able to implement this technology, it would have been cheaper than the $410 million that the city spent to implement the current system. See also: Artificial intelligence; Transportation engineering

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